Principal Data Engineer

Why JamLabs? At JamLabs, we're not just another data consultancy. We're a Toronto-based firm founded by leading engineers and data scientists, with deep roots in capital markets and cloud engineering. Our mission is to transform data into strategic assets for financial services firms, driving growth and innovation through tailored solutions. About the Role You will define and lead projects in the asset management and wealth space, involving large-scale structured and unstructured data, all without legacy constraints. Join our lean, agile team where you'll have the autonomy to shape strategic architecture and drive transformative, high-impact solutions built primarily on the Snowflake Data Cloud. Responsibilities Snowflake Architecture & Governance Leadership: Define the long-term architectural standards for our core data platform in Snowflake. Establish and enforce best practices for data mart creation, leveraging advanced features like Snowpipe, external functions, streams, tasks, clustering, and robust Role-Based Access Control (RBAC). Data Strategy & Platform Modernization: Define the technical roadmap and architectural standards for the data platform, focusing on the migration of data and processes from legacy Azure Data Factory (ADF)/Synapse pipelines to modern, scalable solutions within Snowflake. Design & Build of Critical Pipelines: Architect and oversee the development of highly resilient and scalable ELT pipelines, primarily focusing on efficient ingestion and transformation within the Snowflake platform. Utilize ancillary Azure services and PySpark for pre-ingestion or specialized data preparation tasks only when necessary. Technical Mentorship & Quality Leadership: Lead data-quality initiatives across the organization. Mentor mid-level and senior engineers, and set the standard for data integrity across the Snowflake environment using tools like dbt tests. DevOps & Infrastructure Ownership: Own the automated deployment and lifecycle management of the Snowflake infrastructure and connected Azure services, collaborating with DevOps engineers to implement and manage CI/CD pipelines using Azure DevOps and Dagster, driving initiatives for system stability, reliability, and security. Platform Optimization & Cost Management: Collaborate with the Platform Lead to conduct deep performance tuning and continuous cost optimization within Snowflake (e.g., dynamic warehouse sizing, query optimization) and supporting Azure data services. Cross-Functional Collaboration: Act as the primary technical point of contact for complex, cross-domain data challenges, writing clear, high-level design documents and leading architectural reviews. Qualifications Snowflake Mastery & Design: Expert-level SQL skills and extensive, deep experience with the Snowflake Data Cloud, including complex schema design, advanced performance tuning, and implementing enterprise-level data access controls and data sharing. Data Migration & Modernization: Proven experience in designing and executing successful data migration strategies, particularly involving the transition from legacy technologies (including Azure Synapse/ADF) to modern cloud platforms like Snowflake. Big Data & Processing Knowledge: Proficiency in Spark/PySpark, with knowledge of job tuning and optimization. This is essential for understanding and managing existing pipelines and specialized data preparation, but the focus for new builds is in-warehouse ELT. Cloud Architecture Expertise: Proven ability to architect and scale solutions using Azure services that support the Snowflake ecosystem (e.g., storage, networking, security). Experience with the Azure data stack (ADF/Synapse/Databricks) is required for context and migration. Programming & Engineering Excellence: Expert Python skills, emphasizing writing robust, modular, testable, and reusable code libraries. CI/CD & Engineering Leadership: Mastery of Git-based workflows and driving mature, automated CI/CD pipelines for data deployment using Dagster and Azure DevOps. Familiarity with Infrastructure as Code (IaC) principles. Data Governance & Quality Focus: Demonstrated commitment to data integrity, reliability, and security, including experience defining and implementing governance frameworks. Required Skills Experience in financial services, especially private wealth management. Expertise in dbt (Data Build Tool) for ELT within Snowflake, Airflow, or other modern data orchestration tools. Experience implementing and utilizing advanced observability tools like Datadog or Prometheus for data platforms. Proven experience as a formal mentor, technical lead, or driving agile ceremonies at a team or organizational level. Pay range and compensation package Salary range $180,000-$250,000 CAD depending on qualifications and seniority. We might go outside the range for exceptional candidates. Eligible for performance bonuses. Health and dental benefits. 4 weeks PTO per year. Training budget for certifications and other continued education. Equal Opportunity Statement JamLabs is committed to diversity and inclusivity in the workplace. #J-18808-Ljbffr